Geographic Disparities in Access to Telemedicine Services in the Post-COVID-19 Era

## Rows: 11,932
## Columns: 14
## $ enrlmt_id                 <chr> "I20031103000394", "I20031104000436", "I2003…
## $ npi                       <int> 1790853083, 1356302715, 1356302715, 13564367…
## $ pecos_asct_cntl_id        <dbl> 1254243868, 6507778826, 6507778826, 95370718…
## $ provider_type_desc.before <chr> "PRACTITIONER - FAMILY PRACTICE", "PRACTITIO…
## $ state_cd.before           <chr> "CA", "PA", "PA", "FL", "FL", "FL", "FL", "F…
## $ first_name                <chr> "CORINNE", "PATRICK", "PATRICK", "HUMBERTO",…
## $ mdl_name                  <chr> "VIVIAN", "T", "T", "R", "R", "R", "R", "R",…
## $ last_name                 <chr> "BASCH", "WATERS", "WATERS", "FERNANDEZ MIRO…
## $ gndr_sw                   <chr> "Female", "Male", "Male", "Male", "Male", "M…
## $ city_name                 <chr> "ARCATA", "HUNTINGDON VALLEY", "HUNTINGDON V…
## $ zip_code                  <chr> "95521", "19006", "19006", "33136", "33013",…
## $ rcv_bnft_enrlmt_id        <chr> "O20040121001146", "O20050419000796", "O2018…
## $ provider_type_desc.after  <chr> "PRACTITIONER - GENERAL PRACTICE", "PRACTITI…
## $ state_cd.after            <chr> "CA", "PA", "PA", "FL", "FL", "FL", "FL", "F…

5. Exploratory Data Analysis

5.1 Provider distribution analysis

Analyze how telemedicine-capable providers are distributed across geographic regions on sample data.

## # A tibble: 53 × 2
##    state_cd.before provider_count
##    <chr>                    <int>
##  1 AK                           7
##  2 AL                          97
##  3 AR                          78
##  4 AZ                         208
##  5 CA                        2806
##  6 CO                          45
##  7 CT                          53
##  8 DC                          78
##  9 DE                           5
## 10 FL                         524
## # ℹ 43 more rows

## # A tibble: 2,574 × 2
##    zip_code provider_count
##    <chr>             <int>
##  1 00603                 3
##  2 00612                15
##  3 00617                 1
##  4 00622                 3
##  5 00623                12
##  6 00627                 1
##  7 00641                 3
##  8 00646                 2
##  9 00652                 1
## 10 00656                 2
## # ℹ 2,564 more rows

The provided data offers an overview of the number of providers (provider_count) in each state or region (state_cd.before). Here’s a breakdown of some key observations and interpretations:

1. Wide Variation in Provider Distribution

California (CA) stands out with 2,806 providers, making it by far the state with the highest provider count.
States like Alaska (AK) with 7 providers, Delaware (DE) with 5, and New Hampshire (NH) with 5 have very few providers, which might indicate a smaller healthcare infrastructure or a limited number of provider types.

2. States with Moderate to High Provider Count

States like Florida (FL) with 524, Illinois (IL) with 512, and New Jersey (NJ) with 371 have a higher provider count, reflecting larger populations or possibly a more developed healthcare system.

3. Potential Regional Trends

Larger, more populous states like California, Florida, and Illinois naturally have more providers, likely due to greater demand for healthcare services.
On the other hand, less populous states like Montana (MT) and Nebraska (NE) show lower numbers, which might correlate with their smaller populations or fewer healthcare facilities.

4. Small Providers in Territories or Less Populated Regions

Guam (GU) and Hawaii (HI) have relatively small provider counts of 2 and 32, respectively, which could be attributed to their geographical size or relatively smaller populations.

5. Focus on States with Low Provider Count

States like Montana (MT), Minnesota (MN), and Maine (ME), with 9 to 34 providers, might suggest that healthcare resources are more limited in these regions. This could impact the availability of healthcare services for residents, which may require further investigation or intervention.

The provided data shows the number of healthcare providers (provider_count) available in different zip codes (zip_code). Here are key observations and interpretations:

1. High Provider Counts in Specific Zip Codes

Zip Code 00717 (presumably located in Puerto Rico) has the highest number of healthcare providers with 89 providers, suggesting a higher concentration of healthcare services in this area.
Zip Code 92103 (San Diego, CA) follows closely with 54 providers, indicating a well-developed healthcare infrastructure in this region.

2. Consistent Provider Distribution

Zip Codes 93291, 91767, and 11235 each have a relatively high provider count (around 47-53). These are likely populated or urban areas with better healthcare access.

3. Potential Focus on Specific Urban or Residential Areas

Zip codes like 00917 (San Juan, PR) and 93940 (Monterey, CA) also show strong provider counts (44 and 43, respectively), which might indicate areas of higher population density or healthcare demand.
Zip Code 60639 (Chicago, IL) with 41 providers likely reflects the demand for healthcare services in a major urban center.

4. Lower Provider Counts in Specific Areas

Zip Code 90716 (Compton, CA) with 40 providers and 10003 (New York, NY) with 39 providers still have relatively high counts, though their position at the lower end of the list might indicate the presence of fewer providers in comparison to other areas.

5. Regional Variations

The distribution of provider counts across zip codes is not uniform. Higher counts appear to be in urban or highly populated areas, with fewer providers available in more rural or less populated regions. This suggests that healthcare availability may be more concentrated in metropolitan areas.

Some zip codes, particularly those in neighboring U.S. territories or smaller regions, may not display city names on the chart.

5.2 Geospatial Analysis

Key Observations from the Map

The map clearly shows that North Dakota is highlighted in grey, indicating that there are no providers in the state. This visualization helps identify areas that are underrepresented in terms of provider distribution.

Exploration of Providers by State

We can further explore the data by analyzing the number of providers in each state. This will help us identify which states have the most and least healthcare providers. The analysis can be expanded by looking into provider counts for individual zip codes within each state, which may offer more granular insights.

Here’s a breakdown of the states and their respective provider counts:

California (CA) has the highest provider count with multiple zip codes showing large numbers of providers (e.g., zip codes 00717, 92103, 93291).
Texas, Florida, and New York also show high provider counts, reflecting the density of healthcare services in these states.
North Dakota, as highlighted earlier, has no providers, which indicates a possible gap in healthcare accessibility that could be worth investigating.

5.3 Reassignment by providers

Top Providers by Number of Reassignments

The table below identifies the top providers with the most reassignments:

The provider I20051024000964 in Illinois has the highest number of reassignments (152).
The General Practice specialty seems to have the most reassignments across states, particularly in Illinois and Ohio.

California’s Provider Distribution

When filtering for California in the data, several specialties emerge with a high number of reassignments. Some of the top providers in California include:

Psychiatry (92 reassignments), Hospitalist (70 reassignments), and Anesthesiology (60 reassignments) are among the specialties with the most reassignments in California.
This suggests a higher demand for healthcare providers in these fields, likely driven by the state’s large population and diverse healthcare needs.

Specialties with High Reassignments

Several specialties appear frequently in the top reassignments list, especially: - Psychiatry - Anesthesiology - General Practice

These fields seem to experience a higher frequency of reassignments, potentially due to factors such as provider shortages, burnout, or systemic challenges in the healthcare system.

5.4 Reassignment providers and receivers relationship

Sankey diagram depicting flow of reassignments between providers

Top Providers with Most Reassignments:

The provider O20240201001450 in Ohio (specialty: Dermatology) leads the list with 122 reassignments.
Other providers in New York (NY) and California (CA) also show high numbers of receiving reassignments, particularly in specialties like Interventional Pain Management, Internal Medicine, and Addiction Medicine.

Specialties with Frequent Reassignments:

Addiction Medicine and Geriatric Medicine in California appear frequently with 23 reassignments each.
Physical Medicine and Rehabilitation is another common specialty in Illinois, with multiple providers having 19 reassignments.

Geographical Distribution:

California and Illinois have numerous providers with significant numbers of receiving reassignments, suggesting these states have higher provider turnover or redistribution.
Ohio and New York also emerge as key states, with providers in Dermatology, Interventional Pain Management, and Internal Medicine showing notable reassignment counts.

Conclusion

The data highlights significant disparities in the distribution of healthcare providers across the U.S., with urbanized states such as California, Illinois, and Ohio having a higher number of providers and frequent reassignments. These states are likely home to larger healthcare systems with dynamic provider turnover, suggesting an active healthcare environment. Conversely, states like North Dakota, with no data on providers, may indicate either missing data or gaps in healthcare coverage that warrant further investigation.

The analysis also reveals that California and Illinois exhibit frequent reassignments in specialties such as Dermatology, Pain Management, and Physical Medicine, which could suggest a higher volume of healthcare activity or challenges such as provider shortages or network realignments. Smaller or rural states, where provider numbers are lower, may be underserved, and this could have implications for healthcare access, availability, and quality.

In summary, the data underscores the need for policy interventions to address provider distribution imbalances. This includes focusing on areas with fewer providers and higher reassignment frequencies, potentially through targeted resource allocation, improved retention strategies, and support for underserved regions. Additionally, understanding the trends in specialized care can help inform healthcare planning and ensure that all regions have adequate access to necessary medical services.